Project Summary/Abstract Atypical responses to sensory stimuli are highly prevalent in autism spectrum disorders (ASD). Somatosensory sensitivities in particular occur prominently and with high frequency in the disorder. While core symptomatology is comprised of both sensory dysfunctions and sociocommunicative deficits, the impact of aberrant somatosensory and multisensory processing on sociocommunication abilities remains unknown. It is not well-understood how sensory discrimination anomalies predict later sociocommunicative impairment, or which manifestations of sensory abnormalities result in more severe outcomes. Thus, the objective of this proposal is to investigate the behavioral and neural patterns underlying somatosensory and multisensory discrimination abnormalities longitudinally in young children with ASD compared to TD peers at 4-5 years and 6-7 years of age and identify potential patterns of developmental causality between sensory and sociocommunicative impairments. We theorize that behavioral dysfunction and disruptions in functional and structural connectivity between neural systems in ASD interfere with normative development. Within this theoretical framework, we make three key predictions regarding sensory processing in ASD: (1) Behavioral manifestations of sensory discrimination anomalies in ASD will be objectively observable and quantifiable; (2) functional and structural connectivity patterns within and between sensory and multisensory networks will be atypical; and (3) these atypical network connections will be linked to behavioral manifestations of sensory abnormalities, and combined will predict later sociocommunicative impairments. To examine these hypotheses, we propose a longitudinal and multimodal approach, including behavioral measures, task-based functional magnetic resonance imaging (fMRI), resting state functional connectivity MRI (fcMRI), diffusion weighted imaging (DWI), and neuropsychological indices, along with machine- learning methods, which will be able to reveal distinct patterns within and across modalities, and pinpoint patterns that may most heavily impact autism symptomatology in young children. The distinct strengths of this proposal lie in the application of quantitative behavioral measures to examine sensory discrimination thresholds in young developmental populations, in combination with the use of advanced neuroimaging tools to measure functional activity and (functional and structural) network connectivity between multiple brain systems and the implementation of machine-learning predictive approaches. The proposed training plan incorporates analytic approaches to multimodal neuroimaging and machine-learning, as well as training in neuropsychological evaluation and assessment, which are essential to the applicant's research goals of investigating sensory abnormalities in, and atypical development of, the brain and behavior. This career development award will permit her to develop new expertise necessary for successful completion of the proposed research, while building upon her extensive experience of multisensory development and functional neuroimaging in young children. The Psychology Department at San Diego State University, together with the carefully selected mentorship team, will create an exceptional training environment to further her long-term career goal to become a successful, independent autism researcher in the field of developmental cognitive neuroscience with a focus on sensorimotor processing.